The present invention relates to a camera.
Advances in imaging technology have led to high resolution cameras for personal use as well as professional use. Personal uses include digital cameras and camcorders that can capture high quality images and videos. Professional uses include video conferencing systems and security cameras.
Video conferencing systems have rapidly evolved in capability. As more and more companies look for cost savings, high-tech solutions such as telepresence and video conferencing services are becoming more popular. Telepresence systems deliver lifelike, high-definition images and spatially discrete audio for immersive experiences using advanced visual, audio, and collaboration technologies.
Telepresence is an experience based on videoconferencing. Conventional telepresence systems are expensive as of 2010. Generally costing from $80 to $500K per system, systems creating a telepresence effect provide life-size images of the face and upper body of the remote participants while maintaining a position and proximity perspective that allows the remote participants to appear to be sitting on the other side of a conference-room table.
Another use of high resolution cameras is in video surveillance. The video surveillance equipment market includes CCTV cameras, Digital Video Recorders (DVRs) and Network Video Recorders (NVRs), and IP Encoder/Streamers. The transition from traditional CCTV surveillance to networked digital surveillance is revolutionary for the physical security industry. Network camera systems, for example network surveillance camera systems or IP camera systems, have existed for a number of years but have undergone relatively slow industry adoption. Compared to traditional analog camera systems, network camera systems offer advantages such as accessibility, integration, low installation costs, scalability, and an ability to move to higher resolution video. Data produced by network cameras, however, demand large amounts of bandwidth and storage capacity.
Typical storage architecture of network camera systems is configured similarly to traditional analog systems. The architecture includes centrally located digital video recorders (DVRs) or network video recorders (NVRs) connected through a network to IP cameras. The typical architecture is inadequate for a number of reasons. For example, most DVRs and NVRs do not include open platforms such that a system is limited to one brand for future replacements and upgrades. Also, most DVRs and NVRs do not meet IT standards for system resiliency, redundancy, and long-term archiving of video data. Additionally, typical network camera systems often lack storage scalability such that, as network camera systems expand, storage systems constantly need to be expanded.
Recently, some network camera systems have implemented video analytics processing to identify when important events (such as object movement) are being captured by a video camera. Video analytics has been primarily used to alert security of potential unwanted events. Most video analytics is performed by a central processor that is common to multiple cameras, but some video cameras have built-in video analytics capabilities. These video cameras with built-in analytics, however, have not included large capacity storage due to the large storage requirements of the video data generated by the camera. Also, there are some cameras configured without built-in video analytics but with built-in small storage capacity that is insufficient to serve as a substitute for traditional DVRs and NVRs.
As noted in United States Patent Application 20090219411, video analytics and a mass storage unit are contained in a camera housing of a video camera. The video analytics analyzes video data produced by the video camera and detects whether there is an occurrence of a defined event of interest. The video data representing the field of view of the scene observed by the video camera are stored in the mass storage unit.